IDEAS home Printed from https://ideas.repec.org/a/ibn/ijefaa/v8y2016i3p15-22.html
   My bibliography  Save this article

Time Series Modelling of Inflation in Botswana Using Monthly Consumer Price Indices

Author

Listed:
  • Kesaobaka Molebatsi
  • Mpho Raboloko

Abstract

This paper identifies an autoregressive integrated moving average (ARIMA (1,1,1)) model that can be used to model inflation measured by the consumer price index (CPI) for Botswana. The paper proceeds to improve the model by incorporating the generalized autoregressive conditional heteroscedasticity (ARCH/GARCH) model that takes into consideration volatility in the series. Ultimately, CPI is forecast using the two models, ARIMA (1, 1, 1) and ARIMA (1, 1, 1) + GARCH (1, 2) and compared with the actual CPI. Both models perform well in terms of forecasting as their 95 percent confidence intervals cover the actual CPI. Marginal differences that favour the inclusion of the ARCH/GARCH components were observed when testing for normality among error terms. The paper also reveals that volatility for Botswana¡¯s CPI is low as shown by small values of ARCH/GARCH components.

Suggested Citation

  • Kesaobaka Molebatsi & Mpho Raboloko, 2016. "Time Series Modelling of Inflation in Botswana Using Monthly Consumer Price Indices," International Journal of Economics and Finance, Canadian Center of Science and Education, vol. 8(3), pages 15-22, March.
  • Handle: RePEc:ibn:ijefaa:v:8:y:2016:i:3:p:15-22
    as

    Download full text from publisher

    File URL: http://ccsenet.org/journal/index.php/ijef/article/view/55682/30769
    Download Restriction: no

    File URL: http://ccsenet.org/journal/index.php/ijef/article/view/55682
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
    2. Haile K. Taye, 2013. "Inflation Dynamics in Botswana and Bank of Botswana's Medium-Term Objective Range," Working Papers 36, Botswana Institute for Development Policy Analysis.
    3. Engle, Robert F, 1982. "Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation," Econometrica, Econometric Society, vol. 50(4), pages 987-1007, July.
    4. Atta, J K & Jefferis, K R & Mannathoko, I, 1996. "Small Country Experiences with Exchange Rates and Inflation: The Case of Botswana," Journal of African Economies, Centre for the Study of African Economies, vol. 5(2), pages 293-326, June.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Olalude, Gbenga Adelekan & Olayinka, Hammed Abiola & Ankeli, Uchechi Constance, 2020. "Modelling and forecasting inflation rate in Nigeria using ARIMA models," MPRA Paper 105342, University Library of Munich, Germany, revised Dec 2020.
    2. Nyoni, Thabani & Nathaniel, Solomon Prince, 2018. "Modeling rates of inflation in Nigeria: an application of ARMA, ARIMA and GARCH models," MPRA Paper 91351, University Library of Munich, Germany.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Minot, Nicholas, 2014. "Food price volatility in sub-Saharan Africa: Has it really increased?," Food Policy, Elsevier, vol. 45(C), pages 45-56.
    2. Shively, Gerald E., 2001. "Price thresholds, price volatility, and the private costs of investment in a developing country grain market," Economic Modelling, Elsevier, vol. 18(3), pages 399-414, August.
    3. Tomanova, Lucie, 2013. "Exchange Rate Volatility and the Foreign Trade in CEEC," EY International Congress on Economics I (EYC2013), October 24-25, 2013, Ankara, Turkey 267, Ekonomik Yaklasim Association.
    4. Chang, Chia-Lin, 2015. "Modelling a latent daily Tourism Financial Conditions Index," International Review of Economics & Finance, Elsevier, vol. 40(C), pages 113-126.
    5. Goncalves, Silvia & Kilian, Lutz, 2004. "Bootstrapping autoregressions with conditional heteroskedasticity of unknown form," Journal of Econometrics, Elsevier, vol. 123(1), pages 89-120, November.
    6. Taoufik Bouezmarni & Mohamed Doukali & Abderrahim Taamouti, 2023. "Testing Granger Non-Causality in Expectiles," University of East Anglia School of Economics Working Paper Series 2023-02, School of Economics, University of East Anglia, Norwich, UK..
    7. ?ikolaos A. Kyriazis, 2021. "Impacts of Stock Indices, Oil, and Twitter Sentiment on Major Cryptocurrencies during the COVID-19 First Wave," Bulletin of Applied Economics, Risk Market Journals, vol. 8(2), pages 133-146.
    8. Alagidede, Paul & Panagiotidis, Theodore, 2009. "Modelling stock returns in Africa's emerging equity markets," International Review of Financial Analysis, Elsevier, vol. 18(1-2), pages 1-11, March.
    9. Chang, Chia-Lin & Hsu, Hui-Kuang, 2013. "Modelling Volatility Size Effects for Firm Performance: The Impact of Chinese Tourists to Taiwan," MPRA Paper 45691, University Library of Munich, Germany.
    10. Budi Setiawan & Marwa Ben Abdallah & Maria Fekete-Farkas & Robert Jeyakumar Nathan & Zoltan Zeman, 2021. "GARCH (1,1) Models and Analysis of Stock Market Turmoil during COVID-19 Outbreak in an Emerging and Developed Economy," JRFM, MDPI, vol. 14(12), pages 1-19, December.
    11. Chia-Lin Chang & Michael McAleer, 2017. "A Simple Test for Causality in Volatility," Econometrics, MDPI, vol. 5(1), pages 1-5, March.
    12. Athanasia Gavala & Nikolay Gospodinov & Deming Jiang, 2006. "Forecasting volatility," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 25(6), pages 381-400.
    13. Takahashi, Makoto & Watanabe, Toshiaki & Omori, Yasuhiro, 2016. "Volatility and quantile forecasts by realized stochastic volatility models with generalized hyperbolic distribution," International Journal of Forecasting, Elsevier, vol. 32(2), pages 437-457.
    14. SILVESTRINI, Andrea & VEREDAS, David, 2005. "Temporal aggregation of univariate linear time series models," LIDAM Discussion Papers CORE 2005059, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    15. repec:wyi:journl:002087 is not listed on IDEAS
    16. Chia-Lin Chang & Jukka Ilomäki & Hannu Laurila & Michael McAleer, 2018. "Long Run Returns Predictability and Volatility with Moving Averages," Risks, MDPI, vol. 6(4), pages 1-18, September.
    17. Blazsek, Szabolcs & Escribano, Alvaro, 2023. "Score-driven threshold ice-age models: Benchmark models for long-run climate forecasts," Energy Economics, Elsevier, vol. 118(C).
    18. Beaulieu, Marie-Claude, 1995. "Rendements boursiers et inflation," L'Actualité Economique, Société Canadienne de Science Economique, vol. 71(4), pages 455-480, décembre.
    19. Asai, Manabu & McAleer, Michael, 2015. "Leverage and feedback effects on multifactor Wishart stochastic volatility for option pricing," Journal of Econometrics, Elsevier, vol. 187(2), pages 436-446.
    20. Zeynel Abidin Ozdemir, 2010. "Dynamics Of Inflation, Output Growth And Their Uncertainty In The Uk: An Empirical Analysis," Manchester School, University of Manchester, vol. 78(6), pages 511-537, December.
    21. Mai, Nhat Chi, 2022. "Tác động của lạm phát đến hoạt động của thị trường chứng khoán ở Việt Nam: Kiểm chứng bằng mô hình GARCH," OSF Preprints azcqd, Center for Open Science.

    More about this item

    Keywords

    ARIMA; ARCH; GARCH; CPI; inflation;
    All these keywords.

    JEL classification:

    • R00 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General - - - General
    • Z0 - Other Special Topics - - General

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:ibn:ijefaa:v:8:y:2016:i:3:p:15-22. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Canadian Center of Science and Education (email available below). General contact details of provider: https://edirc.repec.org/data/cepflch.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.